5 minutes read
Nowadays, we have become more familiar with voices that are not human. We ask them random question and chit-chat with them with such ease and smoothness and in return we get answers and responses that help us in getting things done and gain more knowledge either about deep subject matters or about trivia and how the weather is like today.
Those inhuman voices are the virtual assistants that live inside all the gadgets we depend on to make our lives easier.
Not only voice assistants that are becoming an integral part of our lives but also the chatbots and conversational AI platforms with which we text on social media and websites to get our services done.
Such familiarity would not have been realized without a tool that is enabling those assistants to learn the languages of the humans, which is not an easy thing to do because of the complexity of the human interactions.
The human language is a multi-layered way of communication that carries within its layers years of cultural condensation and interactive manifestations that are hard to be grasped at once from a socio and even cognitive angle. Despite this fact, the virtual assistants have proven to be able to handle languages, thanks to the revolution in the world of computational sciences and mathematics that have brought in the brilliant technologies of artificial intelligence and machine learning.
When we talk about the great advances in AI that have made it a reality for virtual assistants to smartly converse with us on a very wide spectrum of topics and issues, we cannot but mention the importance of Natural Language Processing which is a developed branch from the artificial intelligence.
In a paper published in 2001 by the Center for Language Processing in Syracuse University, Prof. Elizabeth DuRoss Liddy, Emeritus Professor of Information Science and former Dean of the Syracuse University School of Information Studies, who is also a pioneer in the field of Natural Language Processing, defines NLP as follows:
“Natural Language Processing is a theoretically motivated range of computational techniques for analyzing and representing naturally occurring texts at one or more levels of linguistic analysis for the purpose of achieving human-like language processing for a range of tasks or applications.”
This definition actually clarifies the ultimate goal for NLP which is to “process” the language of the human beings to turn it into a format that can be easily grasped by the machine and even learnt in order to provide accurate responses within situational and interactive contexts.
As for the level of understanding, comes the NLU or the Natural Language Understanding, which is also a subfield to Artificial Intelligence, and has been created with all intents and purposes to “understand” the language of human beings beyond the literal meaning, which means that NLU has come to introduce an era where machines get the overall context of a conversation. NLU actually gets the sentiment of the conversation and hence specifies intents and goals at a more accurate level. Furthermore, NLU has the ability to to identify the different topics and classify them and even detect the language of communication in addition to translating it.
Natural Language Processing alongside machine learning has given us what has come to be known nowadays as conversational AI which has widely changed the face of the industry of virtual assistants and chatbots. Currently, conversational AI is leading a way to revolutionize chatbots by scaling their potentials with robust data and the ability for understanding diverse intentions and hence contributing to customer experience development.